DESCRIPTION: (Abstract from application) Given our preliminary work, we believe that children of centenarians may be more likely to achieve extreme longevity and, therefore, would prove to be a valuable cohort to study environmental and genetic predispositions to longevity. We have performed genome wide scans on extremely old individuals belonging to several families highly clustered for longevity. Linkage analyses are suggestive of allele sharing for a few specific chromosomal regions. It is likely that some of the children of these individuals will also have the same alleles and, therefore, we can subdivide the children into those who are genetically predisposed to extreme old age by virtue of these alleles and those who are not. We propose to explore the utility, feasibility, optimal study design, and sample size requirements for the longitudinal genetic epidemiologic study of rate-of-change of age-related traits and survival outcomes among these children (Aim 1). In addition to studying the shared alleles as possible genetic risk factors for longevity, we will also explore the utility of specific single nucleotide polymorphisms (SNPs) of selected candidate genes in differentiating between centenarians and controls and between the children with and without the above noted haplotypes (Aim 2). Choosing individuals for study who are less likely to achieve extreme old age (controls) is an important challenge that must be addressed. In addition to the children lacking longevity-associated haplotypes, we want to explore the utility of another potentially useful control group, the children of parents (born in the late 1890's) who died prior to age 80 of non-accidental causes. We propose to compare the children of centenarians and these control group children for differences in the prevalence of age-related phenotypic traits and the prevalence of any candidate gene SNPs that affect the odds of achieving extreme old age (Aim 3). Genetic polymorphisms that affect the rate of incidence of age-related lethal illnesses such as cancer (e.g. genes involved in the replication and DNA repair pathways) would be expected to vary in frequency depending on the age of the population examined. Using disease-specific survival data we propose to mathematically explore relationships between length of survival, certain age-related diseases (especially cancers), expected disease-specific mutation rates, and genes known to affect mutation rates (eg. HRPT, BRCA). Better understanding the subpopulations at risk for specific diseases allows a more informed decision in the choice of candidate genes that may influence longevity (Aim 4). Our fifth aim is to continue our efforts in ascertaining and recruiting families highly clustered for longevity, in collecting phenotype data, and in establishing cell lines.